Innovation Faster Than Implementation

2025 has been a whirlwind for anyone trying to understand how quickly organizations are leaning into AI and what tools they are choosing to get there. Last week I listened to leaders from GE Appliances and Haier along with a former Meta AI engineer here in Louisville. Their experiences matched what I continue to see in the field. The pace of AI innovation is not just fast. It is running away from most companies’ ability to build and implement on their own. After twenty years in technology sales with most of that time spent helping organizations build out infrastructure to store and protect data, I assumed large enterprises would need to build private LLMs inside their own walls for security and compliance.

That idea is becoming harder to defend. The innovation cycles are now so short that building and maintaining a custom LLM is almost impossible for most organizations. Instead many are shifting toward established platforms like OpenAI, Gemini and Claude because these platforms continue to add security, governance and audit features faster than internal teams can keep up. What felt like a requirement to build your own AI model is starting to feel like an anchor that slows progress and adds unnecessary complexity.

Looking ahead to 2026 the path is becoming clear. The major AI platforms are racing to give enterprises everything they need. That includes data isolation, stronger contractual protections, enterprise support, clear audit trails and the ability to fine tune without investing in an entire research division. The lesson for IT and business leaders is straightforward. The winners will not be the companies that build the most models. The winners will be the companies that adopt faster, implement smarter, protect their data and let proven AI platforms handle the heavy lifting. Innovation is not waiting for anyone and the organizations that recognize this will move ahead while everyone else tries to build a model that is already outdated by the time it launches.